Evidence map›Paper›PMID 40465591›Full record

ArticlePLOS digital health2025

Formative evaluation of the acceptance of HIV prevention Artificial Intelligence chatbots by Black gay, bisexual, and other men who have sex with men in the Southern United States: Focus group study.

Jackson Jr Nforbewing Ndenkeh, Gloria A Aidoo-Frimpong, LaRon E Nelson, Mary L Peng, Vimala Balakrishnan, Victoria Barnhart, Bernard Davis, James Donté Prayer, Alvan Quamina, Zhao Ni

Abstract read
In one paragraph

Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Jackson Jr Nforbewing NdenkehSchool of Nursing, Yale University, New Haven, Connecticut, United States of America.ORCID https://orcid.org/0000-0003-1437-660X
Gloria A Aidoo-FrimpongCenter for Interdisciplinary Research on AIDS (CIRA), School of Public Health, Yale University, New Haven, Connecticut, United States of America.
LaRon E NelsonSchool of Nursing, Yale University, New Haven, Connecticut, United States of America.
Mary L PengDepartment of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-9360-5487
Vimala BalakrishnanFaculty of Computer Science and Information Technology, University of Malaya, Malaysia.
Victoria BarnhartCommunity Care Resources of FL (CCRSFL), Pembroke Pines, Florida, United States of America.
Bernard DavisRAO Community Health, Charlotte, North Carolina, United States of America.
James Donté PrayerThe Center for Black Health & Equity, Durham, North Carolina, United States of America.
Alvan QuaminaNational AIDS Education & Services for Minorities (NAESM), Inc, Atlanta, Georgia, United States of America.
Zhao NiSchool of Nursing, Yale University, New Haven, Connecticut, United States of America.ORCID https://orcid.org/0000-0002-9185-9894

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gay, bisexual, and other men who have sex with men (MSM) account for 60% of new HIV infections among Black Americans in the Southern United States (U.S.). Despite recommendations for frequent HIV testing and daily pre-exposure prophylaxis (PrEP) uptake, there remains a gap in PrEP uptake among these Black MSM in the Southern U.S. Artificial Intelligence (AI) chatbots have the potential to boost users' health awareness and medication adherence. This study aims to evaluate Black MSM' perspectives on the challenges to the uptake of PrEP and identify Black MSM-preferred chatbot functionalities and platforms for embedding AI chatbots. Five focus group discussions were conducted (February - March 2024) among 21 Black MSM in the Southern U.S. Interview transcripts were thematically analyzed according to challenges to PrEP uptake and the four domains of the Unified Theory of Acceptance and Use of Technology (UTAUT): performance expectancy, effort expectancy, facilitating conditions, and social influence. Black MSM identified lack of awareness or insufficient information, stigmatizations of sexuality, HIV, and PrEP, as well as concerns with side effects, and low self-perceived HIV vulnerability as the major challenges they faced in PrEP uptake. Moreover, chatbots were perceived as an acceptable option for delivering PrEP education (performance expectancy), especially with accessible, user-friendly interfaces (effort expectancy). Other desired features included simplifying access to PrEP information, incorporating culturally sensitive algorithms, upholding anonymity (social influence), and linking users to healthcare providers and resources (facilitating condition). The study highlights the multifaceted considerations for the adoption of AI chatbots as an HIV-prevention intervention among Black MSM in the Southern U.S.

Identifiers

PMID40465591
PMCPMC12136318

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.